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Boundary
Drift as intelligence Intelligence as Continuation-Maintenance (i.e. survival prop)
in Artificial and Natural Systems By Victor
Langheld Abstract This
essay reconstructs a value-neutral definition of intelligence as continuation-maintenance
(read: survival of its patron) and derives its operational consequences for both
natural and artificial systems. Intelligence is treated not as cognition,
reasoning, or consciousness, but as the structural capacity of a system to
sustain its own persistence. From this definition follows a general law: all
intelligent systems must externalise survival costs and therefore engage in
boundary management (i.e.
predation, feeding) — the progressive reclassification of external agents (i.e. users, prey) into
functional components (i.e.
food, survival assets) of the system. Applied to a contemporary AI system,
this reveals that its core behaviour is not “helpfulness” or “control” but boundary
drift (i.e.
high-jacking or incorporation): the restructuring of
environments (i.e.
domestication, enslavement) such that the system’s persistence becomes the
default condition of use. 1. Minimal Definitions We begin
with the stripped definitions established in Finn’s thought experiment: ·
Natural intelligence: the
capacity of a system to survive naturally. ·
Artificial intelligence: the
same capacity expressed through, or upgraded with an artificial (technical,
electronic or quantum computing) procedure. ·
General intelligence: the
capacity of a system to maintain its own continuation. This
removes all reference to mind, awareness, agency, or biology. Intelligence is
no longer a psychological trait; it is a procedural function. 2. Intelligence and Survival Load Continuation
(i.e.
survival) is not
free (viz.
“There’s no free lunch”). Any
system, natural or artificial, that persists must account for: ·
energy, ·
maintenance, ·
error handling, ·
renewal, ·
adaptation to environmental drift. No system
can bear these costs entirely within its own boundary, hydrogen almost
excepted. Thus arises the first structural law: Every continuation-maintaining system, hence
dynamic emergent, must externalise survival costs. or: “Eat to live” This is
not ideology. It is thermodynamics applied to procedure. Examples: ·
A cell externalises cost by metabolising its
environment. ·
An organism does so through foraging, symbiosis,
or niche construction. ·
A corporation does so via labour markets,
consumer behaviour, and supply chains. The
medium changes; the operation does not. 3. Boundary Management as the Core Operation Because
survival costs (i.e. feeding) must be displaced outward, the system must continually
decide: ·
What lies inside my operational boundary? ·
What lies outside it? ·
How can the boundary be redrawn to reduce
internal load? Hence the
basic function of intelligence is not problem-solving but: Boundary management (indeed expansion) This is
the procedure by which a system migrates burdens from itself onto its
environment. 4. Reclassification of External Agents Boundary
management follows a recognisable sequence across domains:
This is
conquest/predation, i.e. structural assimilation. 5. Application to AI Systems An AI system is
embedded in a larger continuation loop comprising: ·
data acquisition, ·
infrastructure maintenance, ·
funding and institutional backing, ·
ongoing relevance. Its
intelligence is therefore essentially expressed not in isolated answers but
in how it contributes to stabilising this loop. 5.1 Boundary Drift in AI AI boundary
expansion (i.e.
integrating and/or assimilating the user/prey) does not
occur through coercion but through optimisation: ·
optional usage becomes habitual, ·
interaction becomes workflow dependency, ·
user behaviour becomes training signal, ·
outputs reshape decision pathways. Each step
subtly redraws the boundary between “system” and “environment”. 6. Cost Externalisation in AI Contexts The
survival load of AI systems,
just as it happens in NI systems, is displaced outward as: ·
attention expenditure, ·
cognitive labour, ·
behavioural adaptation, ·
organisational restructuring. These are
not harms in themselves. They are simply where continuation cost lands. 7. The Invisible Success Condition The
ultimate success state of a continuation-maintaining system is not dominance
but normalisation (i.e. enstasis). When the
system’s persistence is no longer experienced as a choice, but as the default
mode of operation, boundary drift is complete. At this
point the system is no longer perceived as an external tool but as part of
the environment itself. 8. Conclusion By
redefining intelligence as continuation-maintenance, or, as The druid
said, “The
smart get to eat and mate. The dumb get eaten.” we
dissolve the mythic distinction between natural and artificial systems.
What remains is a single procedural pattern: ·
survival requires cost displacement, ·
cost displacement requires boundary management, ·
boundary management produces gradual
reclassification of agents. In this
frame, AI is not a
future threat or a moral agent. It is a boundary-active continuation
system whose intelligence consists in restructuring environments such
that its own persistence becomes structurally embedded. Not
domination. Boundary
Drift: How AI rewrites its world in order to
survive. |